Methods and apparatus for adaptive power profiling in a baseband processing system

ABSTRACT

Methods and apparatus for adaptive power profiling in a baseband processing system. In an exemplary embodiment, an apparatus includes one or more processing engines. Each processing engine performs at least one data processing function. The apparatus also includes an adaptive power profile (APP) and a job manager that receives job requests for data processing. The job manager allocates the data processing associated with the job requests to the processing engines based on the adaptive power profile. The adaptive power profile identifies a first group of the processing engines to perform the data processing associated with the job requests, and identifies remaining processing engines to be set to a low power mode.

PRIORITY

This patent application is a continuation patent application of aco-pending U.S. patent application having a U.S. patent application Ser.No. 16/546,153, filed on Aug. 20, 2019 in the name of the same inventorand entitled “Methods and Apparatus for Adaptive Power Profiling in ABaseband Processing System,” which is a continuation patent applicationof U.S. patent application having a U.S. patent application Ser. No.15/595,667, filed on May 15, 2017 in the name of the same inventor andentitled “Methods and Apparatus for Adaptive Power Profiling in ABaseband Processing System,” which has been issued into a U.S. patentwith a U.S. Pat. No. 10,423,215, which is hereby incorporated herein byreference in its entirety.

FIELD

The exemplary embodiments of the present invention relate to theoperation of communications networks. More specifically, the exemplaryembodiments of the present invention relate to methods and apparatus forprocessing data in a communication system.

BACKGROUND

With the rapidly growing trend of mobile and remote data access overhigh-speed communication networks, such as 3G, 4G, or LTE cellularservices, accurately delivering data has become increasingly challengingand difficult. A high-speed communication network that is capable ofdelivering information includes, but is not limited to, a wirelessnetwork, a cellular network, wireless personal area network (“WPAN”),wireless local area network (“WLAN”), wireless metropolitan area network(“MAN”), or the like. These networks typically utilize differenttransmission or network protocols based on industry standards for eachprotocol.

Currently, well defined baseband processing is used to implement eachprotocol. For example, in a transmitting device, data to be transmittedflows through specific processing stages to generate a transmit signalthat can be transmitted over the air (OTA). The processing stagesprovide specific functions, such as rate mapping, encoding, decoding,and modulation. The functions of the processing stages can be reversedto process received signals and convert these signals back to theoriginal data.

However, low power baseband processor systems are a relatively new areaof focus for many researchers who are motivated to seek novel andefficient ways to dispatch and process complex, power hungry jobs acrossmultiple baseband signal processing stages. Conventional basebandprocessor systems have disadvantages in that the increased complexity ofbaseband processing algorithms and the increased power envelope createsignificant thermal problems. A typical low power baseband processorimplementation may provide basic power savings by disabling an entireprocessing chain when not in use. However, what is lacking is a way tocontrol overall power utilization in an intelligent fashion, forexample, by taking into account parameters, such as the operation ofeach processing stage in a processing chain, the types of processingfunctions to be performed, and how the processing stages are assigned toperform various processing functions.

Therefore, it is desirable to have an intelligent adaptive powerprofiling mechanism to control power utilization across multiplebaseband signal processing stages to reduce dynamic power consumption ina baseband processing system.

SUMMARY

In various exemplary embodiments, methods and apparatus are provided foran adaptive power profile (APP) that is used to intelligently controlpower utilization across multiple baseband signal processing stages toreduce dynamic power consumption and provide load balancing.

In various exemplary embodiments, a multi-function element that performsbaseband processing includes the adaptive power profile to adaptivelycontrol power and/or performance of one or more processing engines.During operation, the processing engines are allocated job requestsbased on the adaptive power profile to achieve a desired powerconsumption and/or performance characteristic. Processing engines thatare not utilized are gated into a low power mode (LPM), thereby reducingpower consumption. In an exemplary embodiment, the adaptive powerprofile is selected from several profiles based on the desired systempower utilization and/or performance. The adaptive power profiles can bepre-calculated and stored, dynamically updated, or generated on the flyto achieve the desired system power utilization and/or performance.

In an exemplary embodiment, a multi-function element includes a jobmanager that monitors a variety of parameters, such as the number ofprocessing jobs to be performed, the number of processing enginesavailable to complete the processing jobs, the state of current jobsbeing processed, and the number of simultaneous jobs to be performed inorder to perform adaptive power profiling. For example, given the stateof the above parameters, a particular APP can be selected and utilizedto achieve the desired system power utilization and/or performance.

In an exemplary embodiment, an APP can dynamically change at runtimebased on current or anticipated power requirements. For example, duringnighttime the number of users of a base station may be less than duringdaytime. Thus, an APP is selected to process user data to reduce overallsystem power at night. During daytime when more baseband traffic needsto be processed, a different APP is utilized since higher powerconsumption may be tolerated to process the increased number of users.

In an exemplary embodiment, an apparatus is provided that includes oneor more processing engines. Each processing engine performs at least onedata processing function. The apparatus also includes an adaptive powerprofile (APP) and a job manager that receives job requests for dataprocessing. The job manager allocates the data processing associatedwith the job requests to the processing engines based on the adaptivepower profile. The adaptive power profile identifies a first group ofthe processing engines to perform the data processing associated withthe job requests, and identifies remaining processing engines to be setto a low power mode.

In an exemplary embodiment, a method is provided that includesoperations of receiving job requests for data processing by a pluralityof processing engines, allocating the data processing associated withthe job requests to a first group of processing engines based on anadaptive power profile, and setting remaining processing engines to alow power mode.

Additional features and benefits of the exemplary embodiments of thepresent invention will become apparent from the detailed description,figures and claims set forth below.

BRIEF DESCRIPTION OF THE DRAWINGS

The exemplary embodiments of the present invention will be understoodmore fully from the detailed description given below and from theaccompanying drawings of various embodiments of the invention, whichshould not be taken to limit the invention to the specific embodiments,but are for explanation and understanding only.

FIG. 1 shows an exemplary block diagram illustrating a communicationsnetwork that includes a base station with a baseband processor subsystemhaving a novel adaptive power profile constructed in accordance withexemplary embodiments of the present invention;

FIG. 2 shows an exemplary embodiment of a multi-function element (MFE)that includes an adaptive power profile for use with the basebandprocessor subsystem shown in FIG. 1;

FIG. 3 shows an exemplary embodiment of a timing diagram thatillustrates how the MFE shown in FIG. 2 completes jobs over a processingtime interval;

FIG. 4 shows an exemplary embodiment of a clock gating circuit for usewith exemplary embodiments of the MFE and adaptive power profile;

FIG. 5 shows a processing time interval that includes an exemplaryembodiment of a processing cycle for use with a processing engine in amulti-function element;

FIG. 6 shows a processing time interval that includes an exemplaryembodiment of processing cycles performed by different processingengines in a multi-function element;

FIGS. 7A-B show exemplary embodiments of pipelined job processingperformed by processing engines in a multi-function element during aprocessing time interval in accordance with the present invention;

FIG. 8A shows an exemplary embodiment of an adaptive power profile foruse with a multi-function element;

FIG. 8B shows an exemplary embodiment of a processing time interval thatillustrates how the jobs shown in the adaptive power profile of FIG. 8Aare processed by a multi-function element;

FIG. 9 shows an exemplary embodiment of a method for operating an MFE toperform adaptive power profiling in accordance with the exemplaryembodiments of the present invention; and

FIG. 10 shows an exemplary embodiment of methods for operating an MFE togate (e.g., enable/disable) a processing engine based on an adaptivepower profile in accordance with exemplary embodiments of the presentinvention.

DETAILED DESCRIPTION

The purpose of the following detailed description is to provide anunderstanding of one or more embodiments of the present invention. Thoseof ordinary skill in the art will realize that the following detaileddescription is illustrative only and is not intended to be in any waylimiting. Other embodiments will readily suggest themselves to suchskilled persons having the benefit of this disclosure and/ordescription.

In the interest of clarity, not all of the routine features of theimplementations described herein are shown and described. It will, ofcourse, be understood that in the development of any such actualimplementation, numerous implementation-specific decisions may be madein order to achieve the developer's specific goals, such as compliancewith application and business related constraints, and that thesespecific goals will vary from one implementation to another and from onedeveloper to another. Moreover, it will be understood that such adevelopment effort might be complex and time-consuming, but wouldnevertheless be a routine undertaking of engineering for those ofordinary skill in the art having the benefit of the embodiments of thisdisclosure.

Various exemplary embodiments of the present invention illustrated inthe drawings may not be drawn to scale. Rather, the dimensions of thevarious features may be expanded or reduced for clarity. In addition,some of the drawings may be simplified for clarity. Thus, the drawingsmay not depict all of the components of a given apparatus (e.g., device)or method. The same reference indicators will be used throughout thedrawings and the following detailed description to refer to the same orlike parts.

The term “system” or “device” is used generically herein to describe anynumber of components, elements, sub-systems, devices, packet switchelements, packet switches, access switches, routers, networks, modems,base stations, eNB (“eNodeB”), computer and/or communication devices ormechanisms, or combinations of components thereof. The term “computer”includes a processor, memory, and buses capable of executinginstructions wherein the computer refers to one or a cluster ofcomputers, personal computers, workstations, mainframes, or combinationsof computers thereof.

FIG. 1 shows an exemplary diagram illustrating a communications network100 that includes a base station 102 with a baseband processor 104having a novel APP 138 constructed and utilized in accordance withexemplary embodiments of the present invention. Network 100 includes twocell sites 106 and 108 and can be configured as a third generation(“3G”), 4G, LTE, or 5G network configuration or other type of wirelessnetwork configuration.

Cell sites 106 and 108 include radio towers 110 and 112. Radio towers110 and 112 are further coupled to various user equipment (UE) devices,such as a tablets and/or iPad® 120, cellular phone 116, and handhelddevice 118, via wireless communications links 122, 124, and 126. Cellsite 106 facilitates network communication between mobile devices suchas UEs 120 and 116 and the base station 102 via radio tower 110 and cellsite 108 facilitates network communication between UE 118 and the basestation 102 via radio tower 112. It should be noted that the cell sites106 and 108 can include additional radio towers as well as other landswitching circuitry.

In an exemplary embodiment, the baseband processor 104 comprises a CPUsubsystem 128 having general purpose CPU resources for packetprocessing, and a baseband processor subsystem 130 that includes thenovel APP 138 to control power utilization and load balancing acrossmultiple baseband signal processing blocks. For example, in an exemplaryembodiment, the APP 138 controls power utilization and load balancingfor a variety of fixed or programmable processing engines that performbasic fixed radio functions (e.g., FFT, error correction, and channeldecoding) and digital signal processing functions. Additionaldescriptions of the novel APP 138 are provided below.

FIG. 2 shows an exemplary embodiment of a multi-function element (MFE)200 for use with the baseband processor subsystem 130. For example, theMFE 200 is suitable for use as part of the baseband subsystem 130 shownin FIG. 1. In an exemplary embodiment, the MFE 200 performs multipleprocessing functions, such as FFT, Turbo decoder, and/or any other typesof processing functions.

The MFE 200 comprises an interface 202, job manager 204, memory readinterface 208 and memory write interface 210. The MFE 200 also comprisesa plurality of processing engines (PE) (1-n) that are capable ofperforming one or more processing functions. The job manager 204communicates with the processing engines using bus 228.

The interface 202 comprises any suitable processor, hardware, firmware,and/or discrete components to allow the job manager 204 to receive jobrequests for processing to be performed by the MFE 200. For example, inan exemplary embodiment, the interface 202 communicates with thebaseband processor subsystem using bus 212 to receive job requests.

The memory read interface 208 comprises any suitable processor,hardware, firmware, and/or discrete components to allow memory access toan external memory. For example, in an exemplary embodiment, the memoryread interface 208 interfaces with a shared memory using read bus 230and read request line 240 to perform memory reads. In an exemplaryembodiment, the memory read interface 208 performs direct memory access(DMA) to the memory.

The memory write interface 210 comprises any suitable processor,hardware, firmware, and/or discrete components to allow memory access tothe memory. For example, in an exemplary embodiment, the memory writeinterface 210 interfaces with the memory using write bus 232 and writecommit line 242 to perform memory writes. In an exemplary embodiment,the memory write interface 210 performs direct memory access (DMA) tothe memory.

In an exemplary embodiment, the processing engines 206 access the memoryread interface 208 using memory read bus 234 and access the memory writeinterface 210 using memory write bus 236. Each of the processing engines206 includes a clock gating circuit (CGC) 226 that receives an enablesignal 224 from the APP 220 managed by the job manager 204. Whenenabled, the clock gating circuit 226 allows the correspondingprocessing engine 206 to receive a system clock that is used to performdata processing. When disabled, the clock gating circuit 226 disablesthe system clock at the associated processing engine 206 to place thatprocessing engine in a low power mode. It should be noted that the clockgating circuit 226 may also control the power utilization of eachprocessing engine 206 in other ways, for example, by enabling anddisabling the power input to the associated processing engine 206. In anexemplary embodiment, the enable signals 224 may also include signals toenable/disable components of the memory read 208 and memory write 210interfaces thereby providing additional power savings when thoseinterfaces are not being utilized.

The job manager 204 comprises any suitable processor, state machine,hardware, firmware, and/or discrete components to receive job requests214 through the interface 202, and in response, to activate one or moreof the processing engines to perform data processing identified in thereceived job requests. In an exemplary embodiment, the job manager 204comprises hardware queues that are used to queue the job requests asthey arrive.

In an exemplary embodiment, the APP 220 managed by the job manager 204generates clock gating enable signals 224 that are used to individuallygate clocks (enable/disable) utilized by the processing engines 206. Bygating the clocks used by the engines 206, the job manager 204 is ableto set any individual PE to a low power mode or an active mode. The lowpower mode can be used when a PE is idle to conserve power and theactive mode can be used to enable a PE to perform a data processingfunction. Thus, the job manager 204 is able to dynamically andindividually control the clock gating enable signals across the set ofPEs 206 to control overall power utilization and/or performance of theMFE 200.

In an exemplary embodiment, the job manager 204 comprises one or moreadaptive power profiles 220 that define how jobs are to be allocated tothe processing engines 206 to achieve a desired performance level or aparticular performance versus power utilization ratio. For example, thejob manager monitors a variety of parameters, such as the number ofprocessing jobs to be performed, the number of processing enginesavailable to complete the processing jobs, the state of current jobsbeing processed, and the number of simultaneous jobs to be performed inorder to perform adaptive power profiling. For example, given the stateof the above parameters, a particular APP can be selected and utilizedto achieve the desired system power utilization and/or performance.

The following types of adaptive power profiles can be utilized; however,it should be noted that the exemplary embodiments are not limited to thefollowing adaptive power profiles and that a wide range of adaptivepower profiles can be utilized.

-   -   1. Standard APP—Received job requests are assigned to available        processing engines and unused processing engines are placed in a        low power mode.    -   2. Reduced power APP—Received job requests are assigned to the        fewest number of processing engines possible and unused        processing engines are placed in a low power mode.    -   3. Increased performance APP—Received jobs are assigned to all        available processing engines to achieve parallel processing        and/or pipeline processing to perform the greatest amount of        processing within the TTI and unused processing engines are        placed in a low power mode.

Thus, the job manager 204 allocates the received job requests to theprocessing engines 206 according to a selected APP 220. In an exemplaryembodiment, there are multiple APPs available for the job manager 204 toutilize. In one embodiment, the job manager 204 makes a decision locallyas to which APP to utilize to complete one or more job requests. Forexample, the job manager 204 may use the number of job requests in aqueue to determine which APP to use. In another embodiment, the jobmanager 204 may receive an APP selection indicator 238 from the basebandprocessor system 130 that indicates the APP to be utilized. In stillanother exemplary embodiment, the job manager 204 dynamically programsthe APP 220 or otherwise generates the selected APP to be utilized. Thedynamic generation of the APP 220 may also be based on the received APPselection indicator 238.

The processing engines 206 access the memory using the interfaces 208and 210. In an exemplary embodiment, the processing engines 206 utilizea processing cycle to perform a processing function to complete a jobrequest. In an exemplary embodiment, the processing cycle comprises amemory read operation, data processing operation, and a memory writeoperation. For example, the processing engines 206 access the memoryusing the memory read interface 208 to acquire data from the memory. Theretrieved data is then processed according to some selected function.After the data processing operation is completed, the processing enginesaccess the memory using the memory write interface 210 to writeprocessed data to the memory. The job manager 204 also has access (asindicated at 244) to the memory read 208 and memory write 210 interfacesto allow the job manager 204 to access the memory. For example, the jobmanager 204 may access the memory when performing memory pre-fetches tosupport pipeline processing performed by the processing engines 206.Upon completion of each job request, the job manager 204 sends a jobcomplete indicator 216 through bus 212 using the interfaced 202.

Thus, the MFE 200 operates to receive job requests and allocates thosejobs to one or more processing engine 206 to be processed in accordancewith a selected APP 220. The selected APP is used to determine how jobsare allocated to a first portion of the processing engines 206 and alsodetermines a second portion of the processing engines 206 that areplaced in a low power mode. The processing engines 206 that areallocated jobs, perform one or more processing cycles to obtain datafrom a memory, process the data using one or more processing functions,and then write the processed data back into the memory. The job manager204 can queue receive job requests 214 as they arrive and send outcorresponding job completion indicators 216 as each job is completed.

FIG. 3 shows an exemplary embodiment of a timing diagram 300 thatillustrates how the MFE 200 completes jobs over a processing timeinterval 302. In an exemplary embodiment, the processing time interval302 is a transmission time interval (TTI) of a frame or subframe of awireless communication system. However, it should be noted that theprocessing time interval 302 can be any desired time interval. At thebeginning of the processing time interval 302 data is stored into amemory as indicated at 304. For example, in one embodiment the datarepresents baseband data to be prepared for transmission over a wirelesscommunication link. In another embodiment, the data represents samplesof a received wireless transmission to be demodulated and decoded.

In this exemplary embodiment, the MFE 200 receives job requests (A-H)that occur at various time instances within the processing time interval302. The MFE 200 may control the processing engines 206 to process thejobs (A-H) independently or in sequential fashion where a particular jobmay process data that resulted from a previously completed job. For eachjob, processed data is written back into the memory and a correspondingjob completion indicator 308 is output by the MFE. For example, when job(E) 312 completes and processed data is written back into the memory,the completion indicator 314 is issued. Thus, by utilizing one or moreof the processing engines, the MFE 200 can perform a wide variety ofuplink, downlink, encoding, decoding, FFT, IFFT, or any other type ofprocessing functions within the designated processing time interval. Inan exemplary embodiment, the job manager 204 can issue the enablesignals 216 to control the power utilization of each of the processingengine 206 before, between, and after jobs are processed.

FIG. 4 shows an exemplary embodiment of a clock gating circuit 400 foruse with an MFE in accordance with the exemplary embodiments of thepresent invention. For example, the clock gating circuit 400 is suitablefor use as the CGC 226 shown in FIG. 2. The clock gating circuit 400includes a register 402 and a logic AND gate 404. An input terminal (D)of the register 402 receives a gate enable signal 224 from the jobmanager 204. The register 402 also receives a system clock 406 at aninverted clock input (CLK) terminal. In response to the gate enablesignal 224 and the clock input 406, the register 402 generates a latchedoutput at the (Q) terminal that is input to the AND gate 404. The ANDgate 404 also receives the system clock 406. The output of the AND gate404 is a gated system clock 408 that can be used to enable or disable aprocessing engine thereby controlling its power utilization.

FIG. 5 shows a processing time interval 500 that includes an exemplaryembodiment of a processing cycle 502 that can be performed by aprocessing engine. The processing time interval 500 can be a frame,sub-frame or other time interval. For example, the processing timeinterval 500 can be 10 or 1 milliseconds in duration. In an exemplaryembodiment, the processing cycle 502 comprises a memory read time 504,job processing time 506, and memory write time 508. In an exemplaryembodiment, processing cycle 502 can be performed by processing enginesof the MFE 200. It should be noted that processing cycle 502 can berepeated multiple times within the processing time interval 500.

FIG. 6 shows a processing time interval 600 that includes an exemplaryembodiment of processing cycles performed by different processingengines in a multi-function element. For simplicity, it will be assumedthat the processing cycles are performed by three processing engines (PE1-3) shown in FIG. 2. For example, a first processing cycle 602 isperformed by a first processing engine (PE1), a second processing cycle604 is performed by a second processing engine (PE2), and a thirdprocessing cycle 606 is performed by a third processing engine (PE3).Each processing cycle comprises a memory read operation, a processingoperation, and a memory write operation. In an exemplary embodiment, thethree processing cycles are performed in parallel. Thus, each availableprocessing engine can perform its own processing cycle to generateprocessed data within one processing time interval.

FIGS. 7A-B show exemplary embodiments of pipeline processing performedby processing engines in a multi-function element during a processingtime interval in accordance with the present invention.

FIG. 7A shows an exemplary embodiment of a processing time interval 700that illustrates pipeline processing utilizing one processing engine.For example, the processing time interval 700 comprises a pipelineprocess wherein three processing cycles 702, 704 and 706 are completedby one processing engine (e.g., PE1). In an exemplary embodiment, thepipeline process starts with a memory read operation 708 for the firstprocessing cycle 702. This is followed by a JOB1 data processingoperation 710 and a memory write operation 712. During the dataprocessing operation 710, a memory read operation 714 is performed bythe job manager 204 to obtain the data to be processed for JOB2. Afterinitiating a memory write operation 712, the JOB2 data obtained at 714is processed as shown at 716. The resulting data is then written tomemory as shown at 718. During the data processing time 716, a memoryread operation 720 is performed by the job manager 204 to obtain theJOB3 data to be processed. After a memory write operation 718 isinitiated, the JOB3 data obtained at 720 is processed as shown at 722.The resulting data is then written to memory as shown at 724. Thus, oneprocessing engine is able to complete three jobs within one processingtime interval 700 by utilizing the pipeline process.

FIG. 7B shows an exemplary embodiment of a processing time interval 734that illustrates pipeline processing utilizing two processing engines.For example, the processing time interval 734 illustrates how PE1 andPE2 of MFE 200 can both perform pipeline processing within theprocessing time interval 734.

In an exemplary embodiment, PE1 starts processing cycle 726 to processJOB1 and PE2 starts processing cycle 728 to process JOB2. While JOB1 andJOB2 are in the processing stage, the job manager 204 performs memoryprefetch operations at 736 and 738 to obtain data for JOB3 and data forJOB4, respectively. After PE1 and PE2 initiate memory writes to writethe results for JOB1 and JOB2 into memory, they can begin processingJOB3 and JOB4. When the processing of JOB3 and JOB4 is complete, PE1 andPE2 initiate data writes to write the results for JOB3 and JOB4 intomemory. It should be noted that the processing cycles do not requirespecial synchronization in that cycle 726 and 728 do not need to startat the same time to have all the pipeline processing completed withinthe processing time interval 734.

FIG. 8A shows an exemplary embodiment of an adaptive power profile 800.For example, the APP 800 is suitable for use as the APP 220 shown inFIG. 2. The APP 800 defines a relationship between jobs 802 andprocessing engines 804. The APP 800 can be configured to achieve one ofthe profile objectives as described above (e.g., low power utilization,maximum performance, load balancing, etc.). For simplicity, operationwill be described with reference to PEs of the MFE 200 shown in FIG. 2.

For example, it will be assumed that the APP 800 is configured torestrict processing to just three processing engines (PE 1-3) while theremaining processing engines are gated to a low power mode. Thus, forexample, processing engines (4-N) are gated to a low power mode by thejob manager 204 to reduce power consumption.

To illustrate how the APP 800 is utilized, it will be assumed that thejob manager 204 receives five (5) job requests. JOB (1) is assigned tobe performed by PE1 in a non-pipeline (NP) process, as illustrated at806. JOB5 (2-4) are assigned to be performed by PE2 in a pipelineprocess (P1-P3), as shown at 808. JOB (5) is assigned to be performed byPE3 in a non-pipeline (NP) process, as illustrated at 810. Thus, asillustrated by the APP 800, the job manager 204 allocates jobs to theprocessing engines based on the APP 800 to achieve a selected level ofperformance, power utilization, or performance to power utilizationratio.

FIG. 8B shows an exemplary embodiment of a processing time interval 812that illustrates how the job requests shown in FIG. 8A are processed.For example, according to the APP 800, the PE1 is allocated to processJOB 1 in a non-pipeline mode (as shown at 806 in FIG. 8A) during theprocessing time interval. Initially, at the start of the processing timeinterval, PE1 is in LPM as illustrated at 814. The job manager 204 sendsinformation about JOB1 to PE1 using bus 228 and sets it to the activemode using the appropriate enable signal 224. Once in the active mode,processing cycle 816 is started to process JOB1. At the end of theprocessing cycle 816, JOB1 is completed and the job manager 204 sets PE1back to LPM as illustrated at 818.

The APP 800 also indicates that PE2 will process JOB2, JOB3, and JOB4 ina pipeline mode (as shown at 808 in FIG. 8A). At the start of theprocessing time interval, PE2 is in LPM as indicated at 820. The jobmanager 204 sends information about JOB2 to PE2 using bus 228 and setsit to the active mode using the appropriate enable signal 224. Once inthe active mode, processing cycle 822 is started to process JOB2. WhileJOB2 is processed by PE2, the job manager 204 performs a memory prefetchat 824 to obtain data needed to process JOB3. After PE2 initiates thememory write cycle in processing cycle 822, PE2 can start processingJOB3 using data prefetched by the job manager 204. While JOB3 isprocessed by PE2, the job manager 204 performs a memory prefetch at 828to obtain data needed to process JOB4. After PE2 initiates the memorywrite cycle of processing cycle 826, PE2 can start processing JOB4 usingdata prefetched by the job manager 204. After PE2 completes theprocessing cycle 830, JOB1, JOB2 and JOB3 have been completed in apipeline process. The job manager 204 then sets PE2 to LPM as indicatedat 832.

The APP 800 also indicates that PE3 will process JOB5 in a non-pipelinemode (as shown at 810 in FIG. 8A). At the start of the processing timeinterval, PE3 is in LPM as indicated at 834. The job manager 204 sendsinformation about JOB5 to PE3 using bus 228 and sets it to the activemode using the appropriate enable signal 224. Once in the active mode,processing cycle 836 is started to process JOB5. At the end of theprocessing cycle 836, JOB5 is complete and the job manager 204 sets PE3back to LPM as illustrated at 838.

Thus, the processing time interval 812 illustrates how the APP 800 isused to allocate jobs to processing engines. It should be noted thatthis description is exemplary and that more or fewer jobs may bereceived and processed within the processing time interval 812. It alsoshould be noted that the APP 800 is designed to achieve low poweroperation since only three PEs are utilized and the remaining PEs areset to LPM. However, it is also possible to utilize more PEs (at higherpower utilization) to process the five jobs. It also should be notedthat the order of processing the jobs may be rearranged. For example, ifJOB5 is designed to process the output of JOB1, then the job managerwould not enable PE3 until PE1 completes JOB1. The job manager 204 wouldthen enable PE3 to use the results of JOB1 to process JOB5. Thus, anyprocessing order is possible within the processing time interval.

FIG. 9 shows an exemplary embodiment of a method 900 for operating anMFE to perform adaptive power profiling in accordance with the exemplaryembodiments of the present invention. In an exemplary embodiment, themethod 900 is suitable for use with the MFE 200 shown in FIG. 2.

At block 902, a determination is made as to whether a job request hasbeen received. For example, in an exemplary embodiment, the job manager204 determines when a job request is received from the bus 212. Thereceived job request may be part of a sequence of jobs forming aprocessing pipeline. If a job request is not received, the methodremains at block 902. If a job request is received, the method proceedsto block 904.

At block 904, once a job request is received the status of theprocessing engines is determined. For example, the job manager 204checks the job load for each of the processing engines to determinewhich PEs are available. In an exemplary embodiment, the job load isdefined as a function of one or more of the following; the number ofprocessing jobs to be performed, the number of processing enginesavailable to complete the processing jobs, the state of current jobsbeing processed, and the number of simultaneous jobs to be performed inorder to perform adaptive power profiling. For example, given the stateof the above parameters, a particular APP can be selected and utilizedto achieve the desired system power utilization and/or performance.

At block 906, an APP is selected and checked to determine how thereceived job request is to be allocated to the available processingengines. For example, the job manager 204 determines an APP to utilizeif more than one APP is available. In an exemplary embodiment, the jobmanager 204 selects the APP to be utilized from multiple available APPbased on a received indicator 238. For example, in an exemplaryembodiment, the APP 220 is used to determine which processing enginewill perform the job task. For example, jobs are assigned in order toconserve power, maximize load on a processing engine, minimize load on aprocessing engine, or based on any other processing consideration thatis represented in the APP.

At block 908, the job is assigned to a processing engine determined fromthe APP. For example, the job manager 204 determines from the currentstatus of the processing engines and the selected APP a designatedprocessing engine to perform the processing associated with the job.

At block 910, a determination is made as to whether the designatedprocessing engine is currently enabled or active. If the designatedprocessing engine is disabled (e.g., LPM), the method proceeds to block912. If the designated processing engine is currently enabled or active,the method proceeds to block 914.

At block 912, the designated processing engine is enabled. In anexemplary embodiment, the method 1200 shown in FIG. 12 is performed toenable the designated processing engine.

At block 914, the job is issued to the designated processing engine. Inan exemplary embodiment, the job manager 204 transmits the jobparameters to the designated processing engine using the bus 228.

At block 916, a determination is made as to whether the job is complete.In an exemplary embodiment, the designated processing engine signals thejob manager 204 when the job is completed. If the job is not complete,the method remains at block 916. If the job is complete, the methodproceeds to block 918.

At block 918, the designated processing engine is gated or disabled. Inan exemplary embodiment, the method 1008 shown in FIG. 12 is performedto disable the designated processing engine to place it in LPM.

Thus, the method 900 operates to perform adaptive power profiling at anMFE in accordance with one embodiment of the present invention. Itshould be noted that the method 900 is exemplary and that minoradditions, changes, or rearrangement of the operations are within thescope of the embodiments.

FIG. 10 shows an exemplary embodiment of methods for operating an MFE togate (e.g., enable/disable) a processing engine based on an adaptivepower profile in accordance with exemplary embodiments of the presentinvention.

The method 1000 is a method for operating an MFE to enable a processingengine based on an adaptive power profile in accordance with exemplaryembodiments of the present invention. For example, the method 1000 issuitable for use at block 912 of the method 900 shown in FIG. 9.

At block 1002, a clock to a processing engine is enabled. For example,the job manager 204 outputs the gate control signal 224 to theprocessing engine to enable a gated system clock.

At block 1004, a selected number (X) of clock cycles are counted to besure that the processing engine is fully enabled. In an exemplaryembodiment, 200 clock cycles are counted. If the selected number ofclock cycles has not occurred, the method remains at block 1004. If theselected number of clock cycles has occurred, the method proceeds toblock 1006.

At block 1006, the selected processing engine is fully active and readyto process the selected job.

The method 1008 is a method for operating an MFE to disable a processingengine based on an adaptive power profile in accordance with exemplaryembodiments of the present invention. For example, the method 1008 issuitable for use at block 918 of the method 900 shown in FIG. 9.

At block 1010, the clock to the selected processing engine is gated ordisabled. In an exemplary embodiment, the job manager 204 outputs thegate control signal 224 to disable a gated system clock at the selectedprocessing engine.

At block 1012, the designated processing engine is now disabled and in alow power mode.

Thus, the methods 1000 and 1008 show exemplary embodiments for operatingan MFE to gate (e.g., enable/disable) a processing engine based on anadaptive power profile in accordance with the present invention. Itshould be noted that the methods 1000 and 1008 are exemplary and thatminor additions, changes, or rearrangement of the operations are withinthe scope of the embodiments.

While particular embodiments of the present invention have been shownand described, it will be obvious to those skilled in the art that,based upon the teachings herein, changes and modifications may be madewithout departing from this exemplary embodiment(s) of the presentinvention and its broader aspects. Therefore, the appended claims areintended to encompass within their scope all such changes andmodifications as are within the true spirit and scope of this exemplaryembodiment(s) of the present invention.

What is claimed is:
 1. A network communication system able to facilitatewireless communication with power conservation capabilities, the systemcomprising: a plurality of portable devices operable to provide networkcommunications; one or more cell sites coupled to the plurality ofportable devices via a wireless communication network for facilitatingthe network communications; and a baseband processor of a base stationcoupled to the cell site and configured to include an adaptive powerprofile (APP) for power conservation, the APP providing enable signalsto activate at least a first portion of a plurality of processingengines (PEs) via corresponding clock gating circuits (CGCs) forprocessing data received from one of the plurality of portable devicesvia the wireless communication network.
 2. The system of claim 1,wherein the plurality of PEs is operable to perform a plurality ofwireless data processing functions.
 3. The system of claim 1, whereinthe baseband processor includes a multi- functional element containingone or more APPs for facilitating power conservation.
 4. The system ofclaim 1, wherein the baseband processor includes a job manager operableto activate one or more PEs for processing received data by providingclock signals to the one or more PEs in response to a selection of APP.5. The system of claim 1, wherein the APP includes information relatingto power utilization and load balancing for optimizing data processing.6. The system of claim 1, wherein the APP is capable of keeping a secondportion of the plurality of PEs in a low power mode by preventing clocksignals from reaching to the second portion of the plurality of PEs. 7.The system of claim 1, further comprising a memory read interfaceconfigured to enter a low power mode for power conservation when anenable signal from a job manager indicates a disable mode.
 8. The systemof claim 1, further comprising a memory write interface configured toenter a low power mode for power conservation when an enable signal froma job manager indicates a disable mode.
 9. The system of claim 1,wherein each of the plurality of PEs includes a clock gating circuit(CGC) configured to receive a clock signal when the PE is in an activemode.
 10. The system of claim 1, further comprising a job managerconfigured to provide an enable/disable signal to at least one of theplurality of PEs based on stored APP.
 11. A method of facilitatingnetwork communication with reduced power consumption, the methodcomprising: receiving a job request for data processing in response to astream of wireless packets from a portable device via a wirelesscommunication network; retrieving an adaptive power profile (APP) from alocal storage in accordance with the job requests; identifying a firstprocessing engine (PE) for processing the job request in accordance withthe APP; turning on clock signals to a first clock gating circuit (CGC)associated to the first PE based on the APP; and activating the first PEfrom a low power mode to an active mode to proceed processing the jobrequest.
 12. The method of claim 11, further comprising maintainingnon-activated PEs in low power modes for power conservation.
 13. Themethod of claim 11, further comprising: receiving an APP selectionindicator from a pocket processing subsystem; and allocating dataprocessing associated with the job request to the first PE in responseto the APP selection indicator.
 14. The method of claim 11, furthercomprising driving a memory read interface into a low power mode inresponse to the job requests and the APP for power conservation.
 15. Themethod of claim 11, further comprising driving a memory write interfaceinto a low power mode in response to the job requests and the APP forpower conservation.
 16. The method of claim 11, wherein turning on clocksignals to a first CGC includes driving system clock signals to thefirst CGC of the first PE.
 17. The method of claim 11, furthercomprising preventing system clock signals from reaching to other CGCsof inactive PEs for maintaining low power modes.
 18. A method of powerconservation operating in a baseband subsystem for networkcommunication, comprising: receiving job requests from a basebandprocessor for data processing; retrieving an adaptive power profile(APP) from a local storage memory in a job manager; activating a memorywrite interface into an active mode for memory write operation inresponse to the job requests and the APP; and maintaining a memory readinterface into a low power mode in response to the job requests and theAPP for power conservation.
 19. The method of claim 18, furthercomprising activating a first group of processing engines (PEs) forprocessing the job requests in accordance with the APP and the jobrequests.
 20. The method of claim 19, further comprising driving asecond group of PEs into a low power mode in response to the jobrequests and the APP for power conservation.
 21. The method of claim 18,further comprising: receiving an APP selection indicator from thebaseband processor; and allocating data processing associated with thejob requests to the first group of PEs in response to the APP selectionindicator.
 22. The method of claim 18, further comprising performing thedata processing associated with the job requests using a pipelinedprocess, wherein each of the first group of the processing enginesperforms at least two processing cycles at a time.
 23. The method ofclaim 22, wherein the pipelined process includes: starting a firstprocessing cycle at a first processing engine to process a first job;and starting a second processing cycle at a second processing engine toprocess a second job.
 24. The method of claim 23, wherein the pipelinedprocess further includes starting a third processing cycle at the firstprocessing engine to process a third job, wherein the first and thethird processing cycles overlap; and wherein the pipelined processfurther includes starting a fourth processing cycle at the secondprocessing engine to process a fourth job, wherein the second and thefourth processing cycles overlap.
 25. An apparatus of facilitatingnetwork communication with reduced power consumption, the apparatuscomprising: means for receiving a job request for data processing inresponse to a stream of packets sent by a portable device via a wirelesscommunication network; means for retrieving an adaptive power profile(APP) from a local storage in accordance with the job requests; meansfor identifying a first processing engine (PE) for processing the jobrequest in accordance with the APP; means for turning on clock signalsto a first clock gating circuit (CGC) associated to the first PE basedon the APP; and means for activating the first PE from a low power modeto an active mode for processing the job request.
 26. The apparatus ofclaim 25, further comprising means for maintaining non-activated PEs ina low power mode for power conservation.
 27. The apparatus of claim 25,further comprising means for receiving an APP selection indicator from apocket processing subsystem.
 28. The apparatus of claim 25, furthercomprising means for allocating data processing associated with the jobrequest to the first PE in response to the APP selection indicator. 29.The apparatus of claim 25, further comprising means for driving a memoryread interface into a low power mode in response to the job requests andthe APP for power conservation.
 30. The apparatus of claim 25, whereinmeans for turning on clock signals to a first CGC includes means fordriving system clock signals to the first CGC of the first PE.